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In this paper, we fill this gap by presenting a first-of-its-kind holistic risk assessment of different inference attacks against machine learning models. ... Inference attacks against Machine Learning (ML) models allow adversaries to learn sensitive information about training data, model parameters, etc. ... Experimental Evaluation In this section, we build on ML-DOCTOR to provide a holistic assessment of inference attacks against ML models. ...arXiv:2102.02551v2 fatcat:b4mlkrmst5fotgssos7u4dbohy
Data used to train machine learning (ML) models can be sensitive. ... Membership inference attacks (MIAs), attempting to determine whether a particular data record was used to train an ML model, risk violating membership privacy. ... Ml-doctor: Holistic risk assessment of inference attacks cessed: 2021-11-27. against machine learning models. ...arXiv:2112.02230v1 fatcat:zc4vslnrejecxdcpnebn3lally